{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Day07 基础构图元素：标题与网格线\n",
    "\n",
    "　　`标题`与`网格`同样也是绘制一张图非常重要的内容，今天我们就来学习它们："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-20T11:24:59.560936Z",
     "iopub.status.busy": "2020-10-20T11:24:59.560936Z",
     "iopub.status.idle": "2020-10-20T11:24:59.749469Z",
     "shell.execute_reply": "2020-10-20T11:24:59.749469Z",
     "shell.execute_reply.started": "2020-10-20T11:24:59.560936Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "matplotlib版本： 3.3.2\n"
     ]
    }
   ],
   "source": [
    "import matplotlib;print('matplotlib版本：', matplotlib.__version__)\n",
    "import matplotlib.pyplot as plt # 从matplotlib中导入我们最经常使用的pyplot子模块\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] # 设定默认字体为SimHei以解决中文显示乱码问题\n",
    "plt.rcParams['axes.unicode_minus'] = False # 解决图像负号'-'不正常显示的问题"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **设置标题**\n",
    "\n",
    "　　在`matplotlib`中有两种标题，第一种是对应`Axes`对象的标题，可以应用`set_title()`方法进行设置，其部分参数与之前日程学习过的**坐标轴**设置标题功能一样，主要参数如下：\n",
    "  \n",
    "> **label**：字符型，即要设置为标题的文本内容<br>\n",
    "> **fontdict**：字典，用于传入与文字格式相关的参数键值对<br>\n",
    "> **loc**：字符型，控制标题对齐位置，同样有`'center'`、`'left'`和`'right'`三个选项<br>\n",
    "> **pad**：数值型，控制标题距离对应`Axes`区域顶端的像素距离"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-20T11:24:59.751462Z",
     "iopub.status.busy": "2020-10-20T11:24:59.751462Z",
     "iopub.status.idle": "2020-10-20T11:24:59.890054Z",
     "shell.execute_reply": "2020-10-20T11:24:59.889140Z",
     "shell.execute_reply.started": "2020-10-20T11:24:59.751462Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUIAAAFvCAYAAAA/n8J0AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAAVrklEQVR4nO3cf7CddX3g8feHhCgkiKDXYKw4a4mw1m5wuYtKwV7QOGBxbPEHtA5WrZvRKs7sVkbcst1ZRNtBpT+oaKOxpcu2ndhO6aqwVIupaeOvRIqKOspOg2zcrMECMfJDZT/7x/e5uSeHe3NPbs45Se7n/Zo5c88953vO+T4JvOf7nOd5EpmJJFV21KGegCQdaoZQUnmGUFJ5hlBSeYZQUnmGUFJ5hlDSgYtYSsRziHjSoZ7KMITnEUpFRJwPvA54L5nb+p5bBvwj8FEyPzjAez0F+L/A28i8ruc9lgEPk/mTWV6zBDiWzB/0PX4qELN8yv3Ag8Bq4GHg0f53BB4H3Evm/553zvux9GBeLOmIcgZwMfCeOZ6bBL444Hs91PcT4FeAPwYgZuvaXv1P3gk80vdeJwDrgb8A/paZED6xu/8QsIQW3t8Brhpw3rMyhFId/xr4FplfmeW5lwIJXDvge/24+9m78vs08CLgPvaNGsDjgeO6W79HgN8m8+q9j0RsB35E5t/TVn3TK8oHgcvJ/MCA8xyIIZTGLeJY4PvAPWQ+a8SftRQ4pfvt3wBfIuK07vdHyfw2EUcBrwW+B7xqltXcn5H5ne79TqeFa9pE936PA766wF3UR4B3EfGuvsd/1H3mKbSV4NNoK8AkYrIbcz+Zdy3gM/fhd4TSuEW8HLip++1UMr81ws9aBeyY49l/IfNJRLwEuBX4Ovuu5JYDpwEvJHNz9377C8ZxZO5ZwBzvB/4E+FDPo39HC/DlRPwl8Io5Xv0XZP7yAX9mH48aS+P3sjnuj8J02P4DmbH3Bht6nrsMuAc4nczJvTd4Y/d87wrwlcC5TH8XCO8GzgMuBI7qdl/n1o429+8eL6Md8Pjm3lvb9V7W8/l/C0z03b4A7B7kD2E+hlAap4gAfgH4n8B2Rh/C/iOt+z4XcS4tYu8l88d9zx/d/ZwJYeZfkbkJOLF75C4yP0NbdT4A/ISInPPWAndP3+cso+0a9457BjMhfBT4MZn3AmcDF3T3f0I7cHLQ/I5QGq9/B5wE3Ab8H+BSIk4g8z4AIm4Ffh54zt7vviIuA/4AeAuZ1+99p4ifA/4L8Hza92lfBN5B5ld7Pu//7WcuSYvgPwN/RMQTyOxdYT02hO1zlwEv7H57AREvAn4DeBNthTYd1Bd1j/172qkw0A6a9C/AnjPH/KZf07sNvwicD/y3nm04aIZQGq/pFeBngJ3A64ELgD/rHn8j8DVa+F5KxErgXbTvzGbO74t4KfA3wBbgHcAxtOh8gYgzyPxG3+ce1R042fsOAGT+BhHvp+0ev4OIU3pi+LjuZ/+q6yW001sAzqKF7L+T+Uf7jIp4YnfvE2TunPVPox18Sfpj22L5tO7ATe/Rm4dof277bsdBctdYGq+X0XYhb6fFcPqxJvMe4D8CFxDxS8B7af+f/hrTRzbb7vV1tGC+CvgY8KfAr9KC+OuzfO77aSu16dsbej7zu917TQBv7XlN73d0vX6dmd3bPwTuBq4h4igiTiVixWM+vT33vFnm9ZfAPwHf6LvdCWylfSfZ26nHs++u9TKGwBBK4xJxMrAG+BJtRfUwLSLn77Nay9wA3EI7ofhS4O1k3t3zTquBZwKn067u2NXdtnTPr5nl09/dvW769rF9ns28FbgDeBsRj+8enf45syJsMbuAFmJokfwI8ANaSH8PuKe78qTXDcAmIv5V3+M/Rzu3cBntBOm7gctpq9ETu9f1HoB5Vjdm2rGzbOsBM4TS+FzY/XwxM/F6Bu0cuXP6xv4u8GTgX2inlvSa6H7+CbB2ltvbZ/nse8m8a+9t9qOtHwJWApd0v09H5kGAbqX3Udr5hn/c87rfpR3EeJB2BPkLZH6v77030sL6B32P7wE+D/wSmdPfBT6FFrxndZfjTZ9Q/VPAmcD05YE399w/KH5HKI3P9C7wq2lXX0Bbvb2ve67tKkc8jrYr+x3aScRXAVf0vM+93c+HyPz0Pp/QvnNbqD8H1gH/q/v9WOARMqd3jV8DPJu2uzpzvmDmD7vPfgVtZXcd/TI/TsQtwIVEXEDmLd0zTwV+hn2/h7y8u/0QWEE7IBS070ofBj5DxNXAe8h88CC2dy9XhNI4RCynnX/3DTI/Ruanu4hdTzsA0HsazbtpcbiEFsnLiehdMX6LdqT3F4k4vuczVtF2u//zguaY+QBwxt6Tp+EJtO8zp60HXkfmX82yfUfRjhxvp+3Wz+Y/dT/f23O+4TO7n8f3jLuctkg7qZvX12i746+jrT5P6T7ry0QM5cocV4TSeLyEtov3yX0ezXyIiNuAX+guVXsq7WDJ75P5OSJup50y8qdErCFzN5lJxFtpR423EbGeFtM3006jeXfPJ0wfVX1Kz6V10MLz2COu+15q9hR6Q9ieu2GO7Xs97ejxO3p2cfvf+5+I+AzwXNrK8qu0K1cAPkrEBNOLs8xHgT3dkecP01ahnwWuJvNH3alDf9M99/NzzGlgrgil8Zhe8d08y3Of7BlzA22195sAZD5MO8J7Mu0ILd3jN9NWmP9MWwH+V9pBhBeS+eWe954+F/Cd7HtU9pU9zz1WW+E9n5nd8H7TR2un3+N+2nd967vXB+2gDMycVwjtNJ1Tes51PAv4NvDL3XY8HTil58jz7u69Pwm8lMwfddv/5e61b2QIvNZYWswingp8l3aJ3e/1PP4R2gGKJ/U89jTaavIY4N/SdkHfTGbvNcDTY59MO9jz1sf8SzARV9HCuxTYQeZPzTG3o2kHXjaQ+XYiTqLF8HW0I8W3A1+hHRn/Pm21+3jaLvsTaAeNfpp2wGk1mf3/4s3A3DWWFrcf0FZhm/sefz9w4z6PZO4g4um03eZbgXXd5XOzmV4JznYe3/+g7c5/jsceJe7107TL5z7eff5O4C1EXE77KuFM2nelZ9Cidxwt0tN7so/SLrP7ysFEEFwRSjqU2j/1f3/3neChm4YhlFSdB0sklWcIJZVnCCWVZwgllWcIJZVnCCWVZwgllWcIJZVnCCWVZwgllWcIJZVnCCWVZwgllWcIJZVnCCWVZwgllWcIJZVnCCWVZwgllWcIJZVnCCWVZwgllWcIJZVnCCWVZwgllWcIJZVnCCWVZwgllWcIJZVnCCWVZwgllWcIJZVnCCWVZwgllWcIJZVnCCWVZwgllWcIJZVnCCWVZwgllWcIJZVnCCWVN1AII2JlRGzez/NHR8QnImJLRLxheNOTpNGbN4QRcQJwA7B8P8MuA7Zm5lnAhRFx3JDmJ0kjN8iK8FHgYmD3fsZMARu7+1uAyYObliSNz9L5BmTmboCI2N+w5cCO7v5uYGX/gIhYB6wDWL58+RmnnXbagc5VkvZr27Zt92bmxIG+bt4QDmgPcAzwALCi+30fmbkeWA8wOTmZW7duHdJHS1ITEXcv5HXDOmq8DTi7u78G2D6k95WkkTvgFWFEnAc8OzP/sOfhG4CbI+Ic4NnAF4Y0P0kauYFXhJk51f28rS+CZObdwFrgH4EXZ+ajw5ykJI3SsL4jJDO/y8yRY0k6YnhliaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyDKGk8gyhpPIMoaTyBgphRGyIiC0RceUcz58QETdHxOaI+NBwpyhJozVvCCPiImBJZp4FrIqI1bMMuxS4MTPPAY6LiMkhz1OSRmaQFeEUsLG7fxtw9ixjvg+cGhFPBJ4OfKd/QESsi4itEbF1165dC5utJI3AICFcDuzo7u8GVs4y5h+A1cDbgG8C9/UPyMz1mTmZmZMTExMLnK4kDd8gIdwDHNPdXzHHa94DvCkzr6KF8PXDmZ4kjd4gIdzGzO7wGmD7LGOOBX42IpYAzwNyKLOTpDEYJIQ3AZdGxLXAq4E7I+LqvjG/DawHHgBOBP58mJOUpFFaOt+AzNwdEVPAWuCazNwJ3NE35ovAz4xigpI0avOGECAz72PmyLEkLSpeWSKpPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKk8QyipPEMoqTxDKKm8gUIYERsiYktEXDnPuOsj4mXDmZokjce8IYyIi4AlmXkWsCoiVs8x7hzgpMz8+JDnKEkjNciKcArY2N2/DTi7f0BEHA18GNgeES8f2uwkaQwGCeFyYEd3fzewcpYxrwW+DlwDnBkRl/UPiIh1EbE1Irbu2rVrofOVpKEbJIR7gGO6+yvmeM1zgfWZuRO4ETi3f0Bmrs/MycycnJiYWOh8JWnoBgnhNmZ2h9cA22cZcxfwzO7+JHD3Qc9MksZk6QBjbgI2R8Qq4ALgkoi4OjN7jyBvAD4aEZcARwOvHPpMJWlE5g1hZu6OiClgLXBNt/t7R9+YHwCvGsUEJWnUBlkRkpn3MXPkWJIWFa8skVSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFTeQCGMiA0RsSUirpxn3MqIuH04U5Ok8Zg3hBFxEbAkM88CVkXE6v0Mfx9wzLAmJ0njMMiKcArY2N2/DTh7tkERcR7wQ2DnHM+vi4itEbF1165dC5iqJI3GICFcDuzo7u8GVvYPiIhlwG8BV8z1Jpm5PjMnM3NyYmJiIXOVpJEYJIR7mNndXTHHa64APpCZ9w9pXpI0NoOEcBszu8NrgO2zjHkx8JaI2AScHhEfGcrsJGkMlg4w5iZgc0SsAi4ALomIqzNz7xHkzHzh9P2I2JSZbxz6TCVpROYNYWbujogpYC1wTWbuBO7Yz/ipYU1OksZhkBUhmXkfM0eOJWlR8coSSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5RlCSeUZQknlGUJJ5Q0UwojYEBFbIuLKOZ4/PiJuiYhPRcRfR8Sy4U5TkkZn3hBGxEXAksw8C1gVEatnGfYa4NrMXAvsBM4f7jQlaXSWDjBmCtjY3b8NOBv4du+AzLy+59cJ4Hv9bxIR64B1ACeffPICpipJozHIrvFyYEd3fzewcq6BEfEC4ITM/Hz/c5m5PjMnM3NyYmJiQZOVpFEYZEW4Bzimu7+COeIZEScC1wGvGM7UJGk8BlkRbqPtDgOsAbb3D+gOjmwE3pmZdw9tdpI0BoOE8Cbg0oi4Fng1cGdEXN035teAM4DfjIhNEXHxcKcpSaMz765xZu6OiClgLXBNZu4E7ugb80Hgg6OYoCSN2iDfEZKZ9zFz5FiSFhWvLJFUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFSeIZRUniGUVJ4hlFTeQCGMiA0RsSUirjyYMZJ0OJo3hBFxEbAkM88CVkXE6oWMkaTD1SArwilgY3f/NuDsBY6RpMPS0gHGLAd2dPd3A6csZExErAPWdb8+EhFfO7CpHlGeDNx7qCcxQm7fkWsxbxvAqQt50SAh3AMc091fweyryHnHZOZ6YD1ARGzNzMkDnu0Rwu07si3m7VvM2wZt+xbyukF2jbcxs6u7Bti+wDGSdFgaZEV4E7A5IlYBFwCXRMTVmXnlfsY8f9gTlaRRmXdFmJm7aQdDPg+cm5l39EVwtjEPzPO26xc02yOH23dkW8zbt5i3DRa4fZGZw56IJB1RvLJEUnmGUFJ5Iw3hYr80b765R8TxEXFLRHwqIv46IpaNe44HY9C/m4hYGRG3j2tew3AA23Z9RLxsXPMalgH+2zwhIm6OiM0R8aFxz28Yuv/uNu/n+aMj4hPdn8Mb9vdeIwvhYr80b8C5vwa4NjPXAjuB88c5x4NxgH8372PmPNLD3qDbFhHnACdl5sfHOsGDNOD2XQrcmJnnAMdFxBF1bmFEnADcQLuYYy6XAVu7P4cLI+K4uQaOckU4xeK+NG+Keeaemddn5qe6XyeA741nakMxxQB/NxFxHvBDWuiPFFPMs20RcTTwYWB7RLx8fFMbiinm/7v7PnBqRDwReDrwnbHMbHgeBS6mXck2lylm/hy2AHPGfpQh7L/sbuUCxxyuBp57RLwAOCEzPz+OiQ3JvNvX7er/FnDFGOc1DIP83b0W+DpwDXBmRFw2prkNwyDb9w/AauBtwDeB+8YzteHIzN0DnKY38P+jowzhUC7NO4wNNPeIOBG4DtjvdxSHoUG27wrgA5l5/7gmNSSDbNtzgfWZuRO4ETh3THMbhkG27z3AmzLzKloIXz+muY3TwH0ZZXgW+6V58869WzFtBN6ZmXePb2pDMcjfzYuBt0TEJuD0iPjIeKZ20AbZtruAZ3b3J4Ej6e9vkO07FvjZiFgCPA9YjCcUD96XzBzJDXgCcAdwLfCNbiJXzzPm+FHN5xBt35tpuxybutvFh3rew9y+vvGbDvWch/x3dxzwMeCzwOeApx3qeQ95+84E7qStmj4FrDjU817gtm7qfp4HvLXvuWd02/j7wJdoB5BmfZ+RXlnSHdlZC3w22y7GgsYcro7kuQ9iMW/fYt42WPzbN6ju3z84G7g19/OdopfYSSrvSDo4IUkjYQgllWcIJZVnCCWVZwgllff/AegTPaHBnD/GAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 5))\n",
    "\n",
    "ax.set_title('Axe的标题', \n",
    "             fontdict={'fontsize': 20, \n",
    "                       'color': 'red'},\n",
    "             loc='right', pad=50);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　`matplotlib`中的第二种标题是针对整个`Figrue`对象的标题，因为之后的日程中我们会学习到在一个`Figure`图床上布局多个`Axes`对象，所以要区分开这两种标题。\n",
    "\n",
    "　　使用`Figure`对象的`suptitle()`方法来设置最高级别的标题，主要有以下常用参数：\n",
    "  \n",
    "> **t**：字符型，标题内容<br>\n",
    "> **x**：0-1之间，设置标题在x方向上的位置，默认为0.5即为居中<br>\n",
    "> **y**：0-1之间，设置标题在y方向上的位置，默认为0.98即接近上边缘的位置<br>\n",
    "\n",
    "　　其余的有关文字格式的参数不再赘述，下面看一个例子："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-20T11:24:59.891052Z",
     "iopub.status.busy": "2020-10-20T11:24:59.891052Z",
     "iopub.status.idle": "2020-10-20T11:25:00.007739Z",
     "shell.execute_reply": "2020-10-20T11:25:00.006742Z",
     "shell.execute_reply.started": "2020-10-20T11:24:59.891052Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(5, 5))\n",
    "\n",
    "ax.set_title('Axe的标题')\n",
    "\n",
    "fig.suptitle('Figure的标题', \n",
    "             fontdict={'color': 'red'},\n",
    "             x=0,\n",
    "             y=1,\n",
    "             fontsize=40);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **设置网格线**\n",
    "\n",
    "　　给图像添加上网格线，可以作为坐标轴的参考线，在很多情况下可以帮助可视化结果更加直观易读，在`matplotlib`中我们可以利用`Axes`的`grid`方法为所有主要刻度添加参考网格线，默认只为主要刻度添加网格线："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-20T11:25:00.008736Z",
     "iopub.status.busy": "2020-10-20T11:25:00.008736Z",
     "iopub.status.idle": "2020-10-20T11:25:00.227151Z",
     "shell.execute_reply": "2020-10-20T11:25:00.227151Z",
     "shell.execute_reply.started": "2020-10-20T11:25:00.008736Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import ticker\n",
    "\n",
    "x = [i for i in range(10)]\n",
    "y = x\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(x, y)\n",
    "\n",
    "ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.2))\n",
    "ax.grid(True); # 可以看到只有主要刻度才对应生成了网格线"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　而`grid`方法非常类似以前介绍过的`tick_params()`，可以利用`axis`和`which`来指定对哪条坐标轴的哪种刻度生成网格线："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-20T11:25:00.228176Z",
     "iopub.status.busy": "2020-10-20T11:25:00.228176Z",
     "iopub.status.idle": "2020-10-20T11:25:00.386724Z",
     "shell.execute_reply": "2020-10-20T11:25:00.386724Z",
     "shell.execute_reply.started": "2020-10-20T11:25:00.228176Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWkAAAFjCAYAAAD/4PooAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAAsTAAALEwEAmpwYAAAS3klEQVR4nO3df2jkeX3H8de7s5Ed6jVz3p0nOxXl4BiWNdS4g3qkFt1aRymHcWtREIXWkmt7WEphYENtS0t7GxrxDy0nXT39p/aXRzqwRR2l4ahdlJIweANdB/1Dke9yWLUTe8dAQ3j3jyS7l93MzmTynXzeO/N8wEL2O5PPvL9flufNfb+Tb8zdBQCI6edSDwAA6I9IA0BgRBoAAiPSABAYkQaAwIg0AAR2Ks/FHnzwQX/961+f55JH893vSo8+Ohlr5CHKvnA88p0hDxGORV5r5CHxvmxubv7Y3R869EF3z+3P+fPnPak8Xj/KGnmIsi8cj3xnyEOEY5HXGnlIvC+SNrxPVzndAQCBEWkACIxIA0BgRBoAAiPSABAYkQaAwIg0AARGpAEgMCINAIERaQA4hkYr08LKup7PtrSwsq5GK8t1/Vzv3QEA06TRyrS81lZve0eSlHV7Wl5rS5IW58u5vAbvpAFgRKvNzs1A7+tt72i12cntNXKJtJk9bmZXtra28lgOAO4JN7q9I20fRS6Rdver7r40Ozubx3IAcE84UyoeafsoON0BACOq1yoqzhQObCvOFFSvVXJ7DS4cAsCI9i8O7p+DLpeKqtcquV00lIg0ABzL4nx5N8rPzurapQu5r8/pDgAIjEgDQGBEGgACI9IAEBiRBoDAiDQABEakASAwIg0AgRFpAAiMSANAYEQaAAIj0gAQGDf9B4DAuOk/AATG6Q4ACIxIA0BgRBoAAiPSABAYkQaAwIg0AARGpAEgMCINAIERaQAIjEgDQGBEGgACO3W3B83sfklflPRqSZvu/sSJTAUAAzRamVabHd3o9nSmVFS9VtHifDn1WLkb9E76w5K+6O5VSfeZWfUEZgKAu2q0Mi2vtZV1e3JJWben5bW2Gq0s9Wi5GxTpn0h6g5mVJL1W0g/HPhEADLDa7Ki3vXNgW297R6vNTqKJxsfcvf+DZq+TdFnSdyT9oqQn3X37tucsSVqSpNMPnD5/7qlz45t2kOvXpbNnJ2ONPETZF45HvjPkIcKxOMYa7az/vevnyiPcMjnx8dh8YnNz74zFHQZF+vOS/tDdf2ZmfyTpRXe/0u/51WrVNzY2RhoyF9WqdNzXj7JGHqLsC8cj3xnyEOFYHGONhZV1Zd3eHdvLpaKuXbpwYnPktYaZ9Y30oNMd90uaM7OCpLdI6l90ADgh9VpFxZnCgW3FmYLqtUqiicZnUKQvS7oiaUvSqyT9w9gnAoABFufLunxxTuVSUabdd9CXL85N5Kc77voRPHf/T0kJTzIDwOEW58sTGeXb8cMsABAYkQaAwIg0AARGpAEgMCINAIERaQAIjEgDQGBEGgACI9IAEBiRBoDAiDQABEakASCwXCJtZo+b2ZWtrf434gYAHF0ukXb3q+6+NDs7wm9EAAD0xekOAAiMSANAYEQaAAIj0gAQGJEGgMCINAAERqQBIDAiDQCBEWkACIxIA0BgRBoAAiPSAI6k0cq0sLKu57MtLaysq9HKUo800U6lHgDAvaPRyrS81lZve0eSlHV7Wl5rS5IW58spR5tYvJMGMLTVZudmoPf1tne02uwkmmjycT9pAEO70e0daTuOj/tJAxjamVLxSNtxfJzuADC0eq2i4kzhwLbiTEH1WiXRRJOPC4cAhrZ/cXD/HHS5VFS9VuGi4RgRaQBHsjhf3o3ys7O6dulC6nEmHqc7ACAwIg0AgRFpAAiMSANAYEQaAAIj0gAQGJEGgMCINAAERqQBIDAiDQCBEWkACIxIA0Bg3PQfAALjpv8AEBinOwAgMCINAIERaQAIjEgDQGBEGgACI9IAEBiRBoDAiDQABEakASAwIg0AgRFpAAjs1LBPNLOnJX3F3a+OcR4AfTRamVabHd3o9nSmVFS9VtHifDn1WBizoSJtZm+T9BoCDaTRaGVaXmurt70jScq6PS2vtSWJUE+4gac7zGxG0mclfd/M3jv+kQDcbrXZuRnofb3tHa02O4kmwkkxd7/7E8w+KunXJf2+pI9JesHdP/2yx5ckLUnS6QdOnz/31LnxTTvI9evS2bOTsUYeouwLx+PY39/O+t+rfa48wi2CIxyLvNbIQ+J92Xxic9Pdq4c9Nkyk/0bSv7r7V83srKS/cveLhz23Wq36xsbGSEPmolqVjvv6UdbIQ5R94Xgc+/sXVtaVdXt3bC+Xirp26cKJzRFyjTwk3hcz6xvpYT7d8T1Jj+yPIekHI00BYGT1WkXFmcKBbcWZguq1SqKJcFKGuXD4jKTPm9kHJc1Iev94RwJwu/2Lg3y6Y/oMjLS7/6+k3zyBWQDcxeJ8mShPIX6YBQACI9IAEBiRBoDAiDQABEakASAwIg0AgRFpAAiMSANAYEQaAAIj0gAQGJEGgMCINAAElkukzexxM7uytdX/xuQAgKPLJdLuftXdl2ZnR/gNEQCAvjjdAQCBEWkACIxIA0BgRBoAAiPSABAYkQaAwIg0AARGpAEgMCINAIERaQAIjEgDQGBEGhhCo5VpYWVdz2dbWlhZV6OVpR4JU+JU6gGA6BqtTMtrbfW2dyRJWben5bW2JGlxvpxyNEwB3kkDA6w2OzcDva+3vaPVZifRRJgm3E8aGOBGt3ek7UCeuJ80MMCZUvFI24E8cboDGKBeq6g4UziwrThTUL1WSTQRpgkXDoEB9i8O7p+DLpeKqtcqXDTEiSDSwBAW58u7UX52VtcuXUg9DqYIpzsAIDAiDQCBEWkACIxIA0BgRBoAAiPSABAYkQaAwIg0AARGpAEgMCINAIERaQAIjEgDQGDc9B8AAuOm/wAQGKc7ACAwIg0AgRFpAAiMSANAYEQaAAIj0gAQGJEGgMCINAAERqQBIDAiDQCBEWkACOzUME8ys4clfdXd58c8D3BAo5VptdnRjW5PZ0pF1WsVLc6XU48FnJihIi3pE5KK4xwEuF2jlWl5ra3e9o4kKev2tLzWliRCjakx8HSHmV2Q9JKkF8Y/DnDLarNzM9D7ets7Wm12Ek0EnDxz9/4Pmr1CUlPS+yQ13P3thzxnSdKSJJ1+4PT5c0+dG8+kw7h+XTp7djLWyEOUfRlxjXbW//7kc+URbosb4XjwbyP/NfKQeF82n9jcdPfqYY8NivSfSrru7l8ys+cOi/TLVatV39jYGGnIXFSr0nFfP8oaeYiyLyOusbCyrqzbu2N7uVTUtUsXTmyOXNfg30b+a+Qh8b6YWd9IDzrd8U5JT5rZc5LeaGafG2kCYAT1WkXFmcKBbcWZguq1SqKJgJN31wuH7v4r+1/vvZP+nfGPBOzavzjIpzswzYb9dIcGneoAxmFxvkyUMdX4YRYACIxIA0BgRBoAAiPSABAYkQaAwIg0AARGpAEgMCINAIERaQAIjEgDQGBEGgACI9IAEFgukTazx83sytZW/5u0AwCOLpdIu/tVd1+anR3ht2UAAPridAcABEakASAwIg0AgRFpAAiMSANAYEQaAAIj0gAQGJEGgMCINAAERqQBIDAiDQCBEWkcqtHKtLCyruezLS2srKvRylKPBEylU6kHQDyNVqbltbZ62zuSpKzb0/JaW5K0OF9OORowdXgnjTusNjs3A72vt72j1WYn0UTA9OJ+0rjDjW7vSNsBjA/3k8YdzpSKR9oOYHw43YE71GsVFWcKB7YVZwqq1yqJJgKmFxcOcYf9i4P756DLpaLqtQoXDYEEiDQOtThf3o3ys7O6dulC6nGAqcXpDgAIjEgDQGBEGgACI9IAEBiRBoDAiDQABEakASAwIg0AgRFpAAiMSANAYEQaAAIj0gAQGDf9B4DAuOk/AATG6Q4ACIxIA0BgRBoAAiPSABAYkQaAwIg0AARGpAEgMCINAIERaQAIjEgDQGBEGgACOzXoCWY2K+kfJRUkvSTpA+7+f+MebFo1WplWmx3d6PZ0plRUvVbR4nw59VgAEhnmnfSHJH3S3d8l6QVJ7x7vSNOr0cq0vNZW1u3JJWXdnpbX2mq0stSjAUhkYKTd/Wl3//reXx+S9KPxjjS9Vpsd9bZ3Dmzrbe9otdlJNBGA1Mzdh3ui2WOS/tLdf/W27UuSliTp9AOnz5976lzuQw7t+nXp7Nl7do121v9+3HPlEW4De48fj9xF2BeORf5r5CHxvmw+sbnp7tXDHhsq0mb2Kklfk/Qb7v6Dfs+rVqu+sbEx0pC5qFal475+wjUWVtaVdXt3bC+Xirp26cKJzRFyjTxE2BeORf5r5CHxvphZ30gPPN1hZq+Q9CVJy3cLNI6vXquoOFM4sK04U1C9Vkk0EYDUhrlw+FFJb5L0x2b2nJl9YMwzTa3F+bIuX5xTuVSUafcd9OWLc3y6A5hiAz+C5+6fkfSZE5gF2g01UQawjx9mAYDAiDQABEakASAwIg0AgRFpAAiMSANAYEQaAAIj0gAQGJEGgMCINAAERqQBIDAiDQCB5RJpM3vczK5sbfW/aT0A4OhyibS7X3X3pdnZEX57CACgL053AEBgRBoAAiPSABAYkQaAwIg0AARGpAEgMCINAIERaQAIjEgDQGBEGgACI9IAEBiR3tNoZVpYWdfz2ZYWVtbVaGWpRwIAnUo9QASNVqbltbZ62zuSpKzb0/JaW5K0OF9OORqAKcc7aUmrzc7NQO/rbe9otdlJNBEA7OJ+0pJudHtH2g4AJ4X7SUs6UyoeaTsAnBROd0iq1yoqzhQObCvOFFSvVRJNBAC7uHCoWxcH989Bl0tF1WsVLhoCSI5I71mcL+9G+dlZXbt0IfU4ACCJ0x0AEBqRBoDAiDQABEakASAwIg0AgRFpAAiMSANAYEQaAAIj0gAQGJEGgMCINAAERqQBIDBu+g8AgXHTfwAIjNMdABAYkQaAwIg0AARGpAEgMCINAIERaQAIjEgDQGBEGgACI9IAEBiRBoDAiDQABHYq9QCNVqbVZkc3uj2dKRVVr1W0OF9OPRYAhDDUO2kze8bMvmlmH8/zxRutTMtrbWXdnlxS1u1pea2tRivL82UA4J41MNJmdlFSwd0fk/SImT2a14uvNjvqbe8c2Nbb3tFqs5PXSwDAPc3c/e5PMPuUpK+6+5fN7IOSiu7+hZc9viRpSZJOP3D6/Lmnzg394u2s//2n58oj3Pb0+nXp7Nmjf1/ENfIQZV84HvnOkIcIxyKvNfKQeF82n9jcdPfqYY8NE+lnJH3K3b9tZu+S9CZ3XznsudVq1Tc2NoYebGFlXVm3d8f2cqmoa5cuDL3OywaQjvD6odfIQ5R94XjkO0MeIhyLvNbIQ+J9MbO+kR7mnPSLkop7X79yyO8ZSr1WUXGmcGBbcaageq2S10sAwD1tmOBuSvrlva9/SdL383rxxfmyLl+cU7lUlGn3HfTli3N8ugMA9gzzEbyGpG+Y2RlJ75H01jwHWJwvE2UA6GPgO2l3/5mkt0v6lqR3uDu/bRYATshQP8zi7v8j6Z/HPAsA4Db8WDgABEakASAwIg0AgRFpAAiMSANAYEQaAAIj0gAQGJEGgMAG3gXvSIuZ/bekH4z47Q9K+vExR5iVdNyfiIyyBsfjoEk5HhyL/NeYhOPxOnd/6NBH3D3EH0kbOaxxZYLW4HhM4PHgWHA8jvpn0k53XJ2gNfIQZV84HvnOkIcIxyKvNfIQdl9yPd1xHGa24X1uej2NOB4HcTxu4VgcNOnHI9I76SupBwiG43EQx+MWjsVBE308wryTBgDcKdI7aQDAbYh0MGY2a2ZfMbOvmdm/mNkrUs+Umpk9bGat1HNEYWZPm9njqedIzczuN7Mvm9mGmf1t6nnGJUSkzewZM/ummX089SwBfEjSJ939XZJekPTuxPNE8And+mXIU83M3ibpNe4e5VMRKX1Y0hf3LhreZ2YTefEweaTN7KKkgrs/JukRM3s09UwpufvT7v71vb8+JOlHKedJzcwuSHpJu//BmmpmNiPps5K+b2bvTT1PAD+R9AYzK0l6raQfph1nPJJHWru/P3H/V3N9Tbd+M/lUM7PHJN3v7t9KPUsqe6d6/kTSpdSzBPERSf8l6a8lvdnMPpZ4ntT+Q9LrJP2BpOuSfpp2nPGIEOmfl5Ttff1TSQ8nnCUEM3uVpE9L+u3UsyR2SdLT7t5NPUgQ89r9qbYXJP2dpHcknie1P5P0u+7+F5K+I+m3Es8zFhEi/aJunW98pWLMlMzeu8cvSVp291HvgzIp3inpSTN7TtIbzexziedJ7XuSHtn7uqrR75MzKe6XNGdmBUlvkTSRnydO/jlpM/uIpFe7+yfM7M8lddz975MOlZCZ/Z6kpyR9e2/TZ9z9nxKOFIKZPefub089R0pmdp+kz2v3/zZnJL3f3bO7f9fkMrM3S/qCdk95fFPS+9z9xbRT5S9CpH9B0jck/Zuk90h6q7sf925UADARkkda2v28o6Rfk/Tve+fbAAAKEmkAwOGm+iIdAERHpAEgMCINAIERaQAIjEgDQGD/Dyg7NfVYxKh4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import ticker\n",
    "\n",
    "x = [i for i in range(10)]\n",
    "y = x\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(x, y)\n",
    "\n",
    "ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.5))\n",
    "ax.yaxis.set_minor_locator(ticker.MultipleLocator(0.5))\n",
    "ax.grid(True, axis='x', which='minor', color='red') # 激活x轴次要刻度的网格线\n",
    "ax.grid(True, axis='y', which='major', color='green');  # 激活y轴主要刻度的网格线"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　如果你注意观察，可以发现我们绘制的散点其实是被网格线盖住的，可以使用`set_axisbelow(True)`来强制网格线位于底层，你可以通过比较**注释**下列代码中最后一行前后图像的差异情况："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-20T11:25:00.387721Z",
     "iopub.status.busy": "2020-10-20T11:25:00.387721Z",
     "iopub.status.idle": "2020-10-20T11:25:00.479557Z",
     "shell.execute_reply": "2020-10-20T11:25:00.479557Z",
     "shell.execute_reply.started": "2020-10-20T11:25:00.387721Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(x, y)\n",
    "\n",
    "ax.grid(True)\n",
    "\n",
    "ax.set_axisbelow(True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 课后测验：\n",
    "\n",
    "　　今天的任务比较轻松，请你在下面所给代码的基础上，思考一下下图可能的实现方式并将其复现出来~\n",
    "  \n",
    "<center><img src='imgs/示例.png' width=600></img></center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-20T11:25:00.480511Z",
     "iopub.status.busy": "2020-10-20T11:25:00.480511Z",
     "iopub.status.idle": "2020-10-20T11:25:00.595201Z",
     "shell.execute_reply": "2020-10-20T11:25:00.595201Z",
     "shell.execute_reply.started": "2020-10-20T11:25:00.480511Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "x = np.linspace(-10*np.pi, 10*np.pi, 500)\n",
    "y = np.sin(x)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 5))\n",
    "\n",
    "ax.scatter(x, y)\n",
    "\n",
    "'''你的答案'''\n",
    "ax.set_yticks([-1,1]) \n",
    "ax.set_xticks([i*np.pi for i in range(-10,12,2)]);\n",
    "ax.set_xticklabels([str(i)+'π' for i in range(-10,12,2)]);\n",
    "ax.grid(True)\n",
    "ax.set_axisbelow(True);\n",
    "\n",
    "fig.savefig('示例.png', dpi=300);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 请在今天对应的帖子下回复你的文字代码及绘图结果"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
